1. Field of the Invention
The present invention relates generally to signal analysis devices and, more specifically, to a method and apparatus for improving the language skills of a user.
2. Description of the Related Art
In automatic speech recognition (ASR), a computer-implemented algorithm compares a user's spoken input to a database of speech templates to identify the words and phrases spoken by the user. ASR has many potential applications, including use in automated attendants, speech and language therapy, and foreign language instruction.
When used in an automated attendant application, the ASR algorithm should ideally be able to recognize spoken inputs from users having different accents. The current state of the art makes use of speech templates trained from a large database of spoken inputs corresponding to various accents and using other compensation techniques to improve recognition performance for people with accents.
Unfortunately, in addition to the expense involved in gathering spoken inputs for a wide variety of different accents, the resulting ASR algorithm typically sacrifices quality for quantity. That is, while the ASR algorithm might be able to function at some specified level for more users having a wider range of accents, the ASR algorithm also tends to have a decreased ability to recognize the speech from a user having a particular accent than would be the case if the ASR algorithm relied on speech templates based solely on that particular accent. As a result, the automated attendant might not be able to operate with sufficient accuracy for any of its users, no matter what their accents.
During the past few years, computer-based ASR tools have also been used for speech and language therapy and for foreign language instruction. Although currently available computer-based programs offer several useful features, such as therapy result analysis, report generation, and multimedia input/output, they all have a few key problems that limit their use to the classroom or therapist's office. These problems include: (a) no automatic assessment of phonological disorders; (b) no ability to easily and automatically customize the stimulus material for the specific needs of a student/patient; and (c) high cost. Most speech therapy programs are relatively expensive so as to make them unaffordable for use at home. Since most learning by children occurs when their parents are intimately involved in their therapy or language education, cost barriers to home use can result in less effective therapy/education.